Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "145"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 145 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 26 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 26 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 145, Node N14:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2460009 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.037387 -0.653413 2.762049 -0.188519 0.315837 5.635799 0.018686 -0.688933 0.6302 0.6566 0.3510 nan nan
2460008 digital_ok 0.00% 0.00% 0.00% 0.00% - - -0.173577 -0.600199 2.529756 0.602222 0.322312 2.542085 1.932510 0.154200 0.6762 0.6896 0.3152 nan nan
2460007 digital_ok 0.00% 0.00% 0.00% 0.00% - - -0.063525 -0.424110 2.041776 0.747810 0.113373 1.092028 0.662941 -1.631584 0.6426 0.6639 0.3370 nan nan
2459999 digital_ok 0.00% 98.75% 99.08% 0.00% - - nan nan nan nan nan nan nan nan 0.4105 0.3556 0.2321 nan nan
2459998 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.285445 -0.483947 1.839457 0.574799 0.007484 4.770653 0.217796 -0.075678 0.6221 0.6505 0.3762 nan nan
2459997 digital_ok 100.00% 100.00% 100.00% 0.00% - - nan nan inf inf nan nan nan nan nan nan nan nan nan
2459996 digital_ok 100.00% 0.00% 0.00% 0.00% - - 0.006226 -0.456137 3.035977 -0.459582 0.440173 5.313930 0.004855 -0.528351 0.6348 0.6591 0.3953 nan nan
2459995 digital_ok 100.00% 0.00% 0.00% 0.00% - - -0.406708 -0.511064 2.116957 0.363518 0.117716 8.568281 -0.040063 -0.948313 0.6320 0.6589 0.3773 nan nan
2459994 digital_ok 0.00% 0.00% 0.00% 0.00% - - -0.582585 -0.193137 1.758510 0.843022 0.226138 2.226270 0.123485 -0.815658 0.6286 0.6505 0.3682 nan nan
2459993 digital_ok 0.00% 0.00% 0.00% 0.00% - - -0.849369 -0.132487 1.405008 1.159054 0.082566 2.570449 0.085562 -0.873833 0.6205 0.6540 0.3788 nan nan
2459991 digital_ok 0.00% 0.00% 0.00% 0.00% - - -0.936161 -0.002474 1.531852 1.222261 -0.197080 3.019302 -0.171228 -1.246362 0.6357 0.6522 0.3743 nan nan
2459990 digital_ok 100.00% 100.00% 100.00% 0.00% - - 10.584901 13.101427 9.796233 10.506089 8.844139 11.076158 -0.015561 2.107912 0.0710 0.0310 0.0297 nan nan
2459989 RF_maintenance 100.00% 100.00% 100.00% 0.00% - - 10.355778 13.300838 8.718229 9.601987 7.817299 9.295872 0.262578 1.992932 0.0684 0.0291 0.0287 nan nan
2459988 RF_maintenance 100.00% 100.00% 100.00% 0.00% - - 12.434757 15.539005 10.103550 10.798747 10.543499 13.301593 -0.081007 1.775407 0.0719 0.0291 0.0313 nan nan
2459987 RF_maintenance 100.00% 98.54% 100.00% 0.00% - - 10.262699 13.046457 9.787055 10.646436 6.194673 7.978299 0.510932 3.792566 0.0764 0.0309 0.0345 nan nan
2459986 RF_maintenance 100.00% 99.95% 100.00% 0.00% - - 12.811818 15.987788 10.719881 11.497566 9.418895 11.293896 5.330224 10.419789 0.0859 0.0300 0.0423 nan nan
2459985 RF_maintenance 100.00% 72.27% 100.00% 0.00% - - 15.874524 14.436071 8.805109 10.713487 5.182641 8.633778 0.234332 3.849291 0.1899 0.0302 0.1267 nan nan
2459984 RF_maintenance 100.00% 62.74% 100.00% 0.00% - - 15.774145 14.028727 9.087682 11.091909 7.622572 12.140309 2.170073 4.785875 0.2145 0.0325 0.1453 nan nan
2459983 RF_maintenance 100.00% 99.57% 100.00% 0.00% - - 11.017770 13.658219 9.871064 10.507702 9.075204 11.220927 3.241908 7.653292 0.0809 0.0313 0.0381 nan nan
2459982 RF_maintenance 100.00% 90.76% 100.00% 0.00% - - 9.229661 11.595316 8.389658 8.951189 4.372712 5.259938 2.292095 3.404643 0.1007 0.0301 0.0550 nan nan
2459981 RF_maintenance 100.00% 100.00% 100.00% 0.00% - - 10.216636 12.532052 10.530389 11.185045 10.177579 12.370010 -0.045440 2.240579 0.0753 0.0317 0.0329 nan nan
2459980 RF_maintenance 100.00% 96.16% 100.00% 0.00% - - 10.057815 12.047723 9.456956 10.218724 8.773627 10.792819 4.906745 5.578744 0.0899 0.0323 0.0441 nan nan
2459979 RF_maintenance 100.00% 100.00% 100.00% 0.00% - - 10.418660 12.618478 8.766793 9.562992 8.766196 10.159245 -0.001840 2.148855 0.0663 0.0313 0.0255 nan nan
2459978 RF_maintenance 100.00% 100.00% 100.00% 0.00% - - 10.524845 12.895225 9.520863 10.296008 9.136903 10.999241 -0.276070 2.272718 0.0635 0.0296 0.0259 nan nan
2459977 RF_maintenance 100.00% 100.00% 100.00% 0.00% - - 10.841902 13.579709 9.342531 10.144726 9.017124 11.349691 0.574758 3.201613 0.0748 0.0333 0.0319 nan nan
2459976 RF_maintenance 100.00% 100.00% 100.00% 0.00% - - 10.743814 13.008803 9.839264 10.568995 9.171137 10.913895 0.570218 2.331996 0.0656 0.0307 0.0268 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 145: 2460009

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
145 N14 digital_ok nn Temporal Variability 5.635799 -0.037387 -0.653413 2.762049 -0.188519 0.315837 5.635799 0.018686 -0.688933

Antenna 145: 2460008

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
145 N14 digital_ok nn Temporal Variability 2.542085 -0.600199 -0.173577 0.602222 2.529756 2.542085 0.322312 0.154200 1.932510

Antenna 145: 2460007

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
145 N14 digital_ok ee Power 2.041776 -0.063525 -0.424110 2.041776 0.747810 0.113373 1.092028 0.662941 -1.631584

Antenna 145: 2459999

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
145 N14 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 145: 2459998

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
145 N14 digital_ok nn Temporal Variability 4.770653 -0.285445 -0.483947 1.839457 0.574799 0.007484 4.770653 0.217796 -0.075678

Antenna 145: 2459997

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
145 N14 digital_ok ee Shape nan nan nan inf inf nan nan nan nan

Antenna 145: 2459996

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
145 N14 digital_ok nn Temporal Variability 5.313930 0.006226 -0.456137 3.035977 -0.459582 0.440173 5.313930 0.004855 -0.528351

Antenna 145: 2459995

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
145 N14 digital_ok nn Temporal Variability 8.568281 -0.406708 -0.511064 2.116957 0.363518 0.117716 8.568281 -0.040063 -0.948313

Antenna 145: 2459994

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
145 N14 digital_ok nn Temporal Variability 2.226270 -0.582585 -0.193137 1.758510 0.843022 0.226138 2.226270 0.123485 -0.815658

Antenna 145: 2459993

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
145 N14 digital_ok nn Temporal Variability 2.570449 -0.849369 -0.132487 1.405008 1.159054 0.082566 2.570449 0.085562 -0.873833

Antenna 145: 2459991

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
145 N14 digital_ok nn Temporal Variability 3.019302 -0.936161 -0.002474 1.531852 1.222261 -0.197080 3.019302 -0.171228 -1.246362

Antenna 145: 2459990

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
145 N14 digital_ok nn Shape 13.101427 13.101427 10.584901 10.506089 9.796233 11.076158 8.844139 2.107912 -0.015561

Antenna 145: 2459989

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
145 N14 RF_maintenance nn Shape 13.300838 13.300838 10.355778 9.601987 8.718229 9.295872 7.817299 1.992932 0.262578

Antenna 145: 2459988

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
145 N14 RF_maintenance nn Shape 15.539005 15.539005 12.434757 10.798747 10.103550 13.301593 10.543499 1.775407 -0.081007

Antenna 145: 2459987

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
145 N14 RF_maintenance nn Shape 13.046457 10.262699 13.046457 9.787055 10.646436 6.194673 7.978299 0.510932 3.792566

Antenna 145: 2459986

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
145 N14 RF_maintenance nn Shape 15.987788 15.987788 12.811818 11.497566 10.719881 11.293896 9.418895 10.419789 5.330224

Antenna 145: 2459985

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
145 N14 RF_maintenance ee Shape 15.874524 14.436071 15.874524 10.713487 8.805109 8.633778 5.182641 3.849291 0.234332

Antenna 145: 2459984

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
145 N14 RF_maintenance ee Shape 15.774145 15.774145 14.028727 9.087682 11.091909 7.622572 12.140309 2.170073 4.785875

Antenna 145: 2459983

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
145 N14 RF_maintenance nn Shape 13.658219 11.017770 13.658219 9.871064 10.507702 9.075204 11.220927 3.241908 7.653292

Antenna 145: 2459982

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
145 N14 RF_maintenance nn Shape 11.595316 9.229661 11.595316 8.389658 8.951189 4.372712 5.259938 2.292095 3.404643

Antenna 145: 2459981

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
145 N14 RF_maintenance nn Shape 12.532052 12.532052 10.216636 11.185045 10.530389 12.370010 10.177579 2.240579 -0.045440

Antenna 145: 2459980

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
145 N14 RF_maintenance nn Shape 12.047723 12.047723 10.057815 10.218724 9.456956 10.792819 8.773627 5.578744 4.906745

Antenna 145: 2459979

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
145 N14 RF_maintenance nn Shape 12.618478 10.418660 12.618478 8.766793 9.562992 8.766196 10.159245 -0.001840 2.148855

Antenna 145: 2459978

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
145 N14 RF_maintenance nn Shape 12.895225 12.895225 10.524845 10.296008 9.520863 10.999241 9.136903 2.272718 -0.276070

Antenna 145: 2459977

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
145 N14 RF_maintenance nn Shape 13.579709 10.841902 13.579709 9.342531 10.144726 9.017124 11.349691 0.574758 3.201613

Antenna 145: 2459976

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
145 N14 RF_maintenance nn Shape 13.008803 13.008803 10.743814 10.568995 9.839264 10.913895 9.171137 2.331996 0.570218
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